From a0ebeb7effaf4199a35661f4ee0c085fec8b3ad7 Mon Sep 17 00:00:00 2001
From: Neta Zmora <neta.zmora@intel.com>
Date: Wed, 15 May 2019 17:01:48 +0300
Subject: [PATCH] =?UTF-8?q?Revert=20"SummaryGraph:=20fix=20=E2=80=98weight?=
=?UTF-8?q?s=5Fvol=E2=80=99=20attribute=20for=20conv=20and=20linear=20laye?=
=?UTF-8?q?rs"?=
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This reverts commit a3f2ce2d5199c22dccbe21c870a60e4409b4c490.
---
distiller/summary_graph.py | 25 ++++++++++---------------
tests/test_summarygraph.py | 30 ++++++------------------------
2 files changed, 16 insertions(+), 39 deletions(-)
diff --git a/distiller/summary_graph.py b/distiller/summary_graph.py
index d246fd5..d3facd5 100755
--- a/distiller/summary_graph.py
+++ b/distiller/summary_graph.py
@@ -21,6 +21,7 @@ import collections
import torch
import torch.jit as jit
import logging
+from collections import OrderedDict
msglogger = logging.getLogger()
@@ -99,17 +100,17 @@ class SummaryGraph(object):
device = next(model_clone.parameters()).device
dummy_input = distiller.convert_tensors_recursively_to(dummy_input, device=device)
- trace, _ = jit.get_trace_graph(model_clone, dummy_input)
+ trace, _ = jit.get_trace_graph(model_clone, dummy_input, _force_outplace=True)
# Let ONNX do the heavy lifting: fusing the convolution nodes; fusing the nodes
# composing a GEMM operation; etc.
torch.onnx._optimize_trace(trace, torch.onnx.OperatorExportTypes.ONNX)
graph = trace.graph()
- self.ops = {}
- self.params = {}
+ self.ops = OrderedDict()
+ self.params = OrderedDict()
self.edges = []
- self.temp = {}
+ self.temp = OrderedDict()
in_out = list(graph.inputs()) + list(graph.outputs())
for param in in_out:
@@ -148,7 +149,7 @@ class SummaryGraph(object):
self.__add_output(new_op, output)
self.edges.append(SummaryGraph.Edge(new_op['name'], output.uniqueName()))
- new_op['attrs'] = {attr_name: node[attr_name] for attr_name in node.attributeNames()}
+ new_op['attrs'] = OrderedDict([(attr_name, node[attr_name]) for attr_name in node.attributeNames()])
self.add_macs_attr()
self.add_footprint_attr()
@@ -156,7 +157,7 @@ class SummaryGraph(object):
del model_clone
def __create_op(self, onnx_node):
- op = {}
+ op = OrderedDict()
op['name'] = onnx_node.scopeName()
op['orig-name'] = onnx_node.scopeName()
op['type'] = onnx_node.kind().lstrip('::onnx')
@@ -188,7 +189,7 @@ class SummaryGraph(object):
return param
def __tensor_desc(self, n):
- tensor = {}
+ tensor = OrderedDict()
tensor['id'] = n.uniqueName()
try:
# try parsing the FM tensor type. For example: Float(1, 64, 8, 8)
@@ -245,14 +246,8 @@ class SummaryGraph(object):
ofm_vol = self.param_volume(conv_out)
ifm_vol = self.param_volume(conv_in)
if op['type'] == 'Conv' or op['type'] == 'Gemm':
- if op['type'] == 'Conv':
- kernel_size = self.volume(op['attrs']['kernel_shape'])
- group = op['attrs']['group']
- else:
- kernel_size, group = 1, 1
- n_ifm = self.param_shape(conv_in)[1] / group
- n_ofm = self.param_shape(conv_out)[1]
- weights_vol = kernel_size * n_ifm * n_ofm
+ conv_w = op['inputs'][1]
+ weights_vol = self.param_volume(conv_w)
op['attrs']['footprint'] = ofm_vol + ifm_vol + weights_vol
op['attrs']['fm_vol'] = ofm_vol + ifm_vol
op['attrs']['weights_vol'] = weights_vol
diff --git a/tests/test_summarygraph.py b/tests/test_summarygraph.py
index f74bfda..8cf1e7d 100755
--- a/tests/test_summarygraph.py
+++ b/tests/test_summarygraph.py
@@ -116,24 +116,6 @@ def test_layer_search():
assert preds == ['layer1.0.conv2', 'conv1']
-def test_weights_size_attr():
- def test(dataset, arch, dataparallel:bool):
- model = create_model(False, dataset, arch, parallel=False)
- sgraph = SummaryGraph(model, get_input(dataset))
-
- distiller.assign_layer_fq_names(model)
- for name, mod in model.named_modules():
- if isinstance(mod, torch.nn.Conv2d) or isinstance(mod, torch.nn.Linear):
- op = sgraph.find_op(name)
- assert op is not None
- assert op['attrs']['weights_vol'] == distiller.volume(mod.weight)
-
- for data_parallel in (True, False):
- test('cifar10', 'resnet20_cifar', data_parallel)
- test('imagenet', 'alexnet', data_parallel)
- test('imagenet', 'resnext101_32x4d', data_parallel)
-
-
def test_vgg():
g = create_graph('imagenet', 'vgg19')
assert g is not None
@@ -188,11 +170,11 @@ def named_params_layers_test_aux(dataset, arch, dataparallel:bool):
def test_named_params_layers():
- for data_parallel in (True, False):
- named_params_layers_test_aux('imagenet', 'vgg19', data_parallel)
- named_params_layers_test_aux('cifar10', 'resnet20_cifar', data_parallel)
- named_params_layers_test_aux('imagenet', 'alexnet', data_parallel)
- named_params_layers_test_aux('imagenet', 'resnext101_32x4d', data_parallel)
+ for dataParallelModel in (True, False):
+ named_params_layers_test_aux('imagenet', 'vgg19', dataParallelModel)
+ named_params_layers_test_aux('cifar10', 'resnet20_cifar', dataParallelModel)
+ named_params_layers_test_aux('imagenet', 'alexnet', dataParallelModel)
+ named_params_layers_test_aux('imagenet', 'resnext101_32x4d', dataParallelModel)
def test_onnx_name_2_pytorch_name():
@@ -231,4 +213,4 @@ def test_sg_macs():
if __name__ == '__main__':
#test_connectivity_summary()
- test_sg_macs()
+ test_sg_macs()
\ No newline at end of file
--
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